Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2021 , Vol. 55 >Issue 12: 1673 - 1688

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2021.397

Optimal Sizing and Placement of Distributed Generation Based on Adaptive Manta Ray Foraging Optimization

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  • 1. School of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
    2. School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
    3. Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid, Guangzhou 510640, China

Received date: 2021-10-08

  Online published: 2021-12-30

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Abstract

In this paper, an optimal sizing and placement model for distributed generation (DG) is established, which includes active power losses, voltage profile, pollution emission, DG costs, and meteorological conditions. Since optimizing placement and sizing are discrete and continuous variables respectively, the model established is a highly nonlinear complex one with discrete optimization variables. Therefore, the adaptive manta ray foraging optimization (AMRFO) algorithm is applied to obtain the optimal Pareto front, which has a rich and diverse search mechanism, individual updating mechanism, and advanced Pareto solution selection mechanism. For this model, a better solution of high quality can be obtained. In order to avoid the influence of subjective setting of weight coefficient, the ideal point method based on Mahalanobis distance is used to make Pareto front decision. Finally, the simulation based on the IEEE 33, 69-bus distribution network and the IEEE 33, 69-bus distribution network in isolated network operation are implemented. The results show that compared with the traditional multi-objective intelligent optimization algorithm, AMRFO algorithm can obtain a more widely distributed and uniform Pareto front. While considering the economy, the optimized distribution network voltage profile and active power losses can be significantly improved.

Key words： distribution network; distributed generation (DG); optimal sizing and placement; adaptive manta ray foraging optimization (AMRFO) algorithm

Cite this article

YANG Bo, YU Lei, WANG Junting, SHU Hongchun, CAO Pulin, YU Tao . Optimal Sizing and Placement of Distributed Generation Based on Adaptive Manta Ray Foraging Optimization[J]. Journal of Shanghai Jiaotong University, 2021 , 55(12) : 1673 -1688 . DOI: 10.16183/j.cnki.jsjtu.2021.397

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